Josh Dillon, Last Revised January 2022
This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')
antenna = "132" csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_" auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')
Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_ Found 33 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0
def jd_to_summary_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'
def jd_to_auto_metrics_url(jd):
return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'
this_antenna = None
jds = []
# parse information about antennas and nodes
for csv in csvs:
df = pd.read_csv(csv)
for n in range(len(df)):
# Add this day to the antenna
row = df.loc[n]
if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
else:
antnum = int(row['Ant'])
if antnum != int(antenna):
continue
if np.issubdtype(type(row['Node']), np.integer):
row['Node'] = str(row['Node'])
if type(row['Node']) == str and row['Node'].isnumeric():
row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
if this_antenna is None:
this_antenna = Antenna(row['Ant'], row['Node'])
jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
jds.append(jd)
this_antenna.add_day(jd, row)
break
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]
df = pd.DataFrame(to_show)
# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
df[col] = bar_cols[col]
z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
df[col] = z_score_cols[col]
ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
df[col] = ant_metrics_cols[col]
redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]
for col in redcal_cols:
df[col] = redcal_cols[col]
# style dataframe
table = df.style.hide_index()\
.applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
.background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
.background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
.applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
.applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
.bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
.format({col: '{:,.4f}'.format for col in z_score_cols}) \
.format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
.format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
.set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])
This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))
| JDs | A Priori Status | Auto Metrics Flags | Dead Fraction in Ant Metrics (Jee) | Dead Fraction in Ant Metrics (Jnn) | Crossed Fraction in Ant Metrics | Flag Fraction Before Redcal | Flagged By Redcal chi^2 Fraction | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | Average Dead Ant Metric (Jee) | Average Dead Ant Metric (Jnn) | Average Crossed Ant Metric | Median chi^2 Per Antenna (Jee) | Median chi^2 Per Antenna (Jnn) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2460016 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.217124 | -0.021670 | -0.536486 | -1.315919 | -0.378832 | -0.950438 | -0.066986 | -0.130622 | 0.5364 | 0.5365 | 0.3492 | nan | nan |
| 2460015 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.197958 | 0.271858 | -0.473943 | -1.209921 | -0.287555 | -0.764425 | 0.671223 | -0.056586 | 0.5481 | 0.5447 | 0.3476 | nan | nan |
| 2460014 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.923065 | 0.655349 | -0.922511 | -1.159732 | 0.334038 | -0.733697 | 2.578954 | 0.333649 | 0.5142 | 0.5203 | 0.3464 | nan | nan |
| 2460013 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.407297 | -0.030984 | -0.615244 | -1.329978 | 0.322798 | -0.265497 | -0.851625 | -0.436433 | 0.5404 | 0.5449 | 0.3540 | nan | nan |
| 2460012 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.301787 | -0.161551 | -0.486829 | -1.459222 | -0.754782 | -0.250714 | -0.745751 | -0.616751 | 0.5470 | 0.5487 | 0.3505 | nan | nan |
| 2460011 | not_connected | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460010 | not_connected | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460009 | not_connected | 100.00% | 99.95% | 99.95% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | 0.8211 | 0.5799 | 0.6683 | nan | nan |
| 2460008 | not_connected | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2460007 | not_connected | 100.00% | 100.00% | 100.00% | 0.00% | - | - | nan | nan | inf | inf | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| 2459999 | not_connected | 0.00% | 0.08% | 0.00% | 0.00% | - | - | nan | nan | nan | nan | nan | nan | nan | nan | 0.6009 | 0.5876 | 0.3049 | nan | nan |
| 2459998 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.903739 | 0.235142 | -0.336024 | -1.165780 | -0.506575 | -0.789389 | 0.346730 | -0.168208 | 0.5754 | 0.5856 | 0.3719 | nan | nan |
| 2459997 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.724379 | 0.136086 | 0.050466 | -1.153448 | -1.024379 | -0.821948 | -0.360455 | -0.409545 | 0.5942 | 0.6029 | 0.3741 | nan | nan |
| 2459996 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -1.048155 | -0.046172 | -0.491167 | -1.173534 | -0.351141 | -0.676836 | -0.293716 | -0.355275 | 0.5897 | 0.5995 | 0.3873 | nan | nan |
| 2459995 | not_connected | 100.00% | 99.46% | 99.46% | 0.00% | - | - | 251.368927 | 251.390312 | inf | inf | 3295.470758 | 3294.782826 | 7716.389743 | 7713.477310 | 0.5181 | 0.5645 | 0.3266 | nan | nan |
| 2459994 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.801687 | 0.310606 | -0.169004 | -1.208889 | -0.473073 | -0.665875 | -0.080085 | 0.163766 | 0.5870 | 0.5940 | 0.3698 | nan | nan |
| 2459993 | not_connected | 100.00% | 0.00% | 0.00% | 0.00% | - | - | -0.715404 | 0.395920 | -0.150201 | -1.353123 | 5.535953 | -0.530371 | 0.385604 | -0.469203 | 0.5772 | 0.6069 | 0.3839 | nan | nan |
| 2459991 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.603261 | 0.685740 | -0.215517 | -1.337504 | 1.272804 | -0.938272 | 0.833594 | 0.205311 | 0.5835 | 0.5860 | 0.3796 | nan | nan |
| 2459990 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.473901 | 0.673899 | -0.073268 | -1.331626 | -0.038642 | -0.984190 | 0.192113 | -0.146128 | 0.5797 | 0.5836 | 0.3757 | nan | nan |
| 2459989 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.669825 | 0.723688 | -0.006582 | -1.001843 | 1.463889 | -1.109001 | 0.538090 | -0.392708 | 0.5773 | 0.5853 | 0.3765 | nan | nan |
| 2459988 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.787664 | 0.826369 | -0.071043 | -1.430071 | 0.065768 | -0.831839 | -0.308809 | -0.214164 | 0.5822 | 0.5878 | 0.3699 | nan | nan |
| 2459987 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.972076 | 0.228336 | -0.211240 | -1.310179 | -0.542778 | -0.652055 | -0.853090 | -0.013743 | 0.5918 | 0.5976 | 0.3670 | nan | nan |
| 2459986 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.976993 | 0.597970 | -0.226936 | -1.486124 | 1.087773 | -0.727994 | -0.576139 | -1.547479 | 0.6156 | 0.6287 | 0.3240 | nan | nan |
| 2459985 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.816103 | 0.312475 | -0.528669 | -1.358213 | 0.559127 | -1.162484 | 0.006813 | -0.430300 | 0.5904 | 0.5994 | 0.3741 | nan | nan |
| 2459984 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.631730 | 0.031208 | -0.866793 | -1.378836 | 0.418826 | -0.962083 | -1.272424 | -0.984932 | 0.6019 | 0.6189 | 0.3572 | nan | nan |
| 2459983 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.858002 | 2.229185 | -0.235428 | -1.329347 | 0.434885 | -0.640816 | 0.012368 | -1.109357 | 0.6189 | 0.6348 | 0.3088 | nan | nan |
| 2459982 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | 0.480627 | 1.789049 | -1.145706 | -0.911906 | 0.787062 | -1.012047 | -0.671433 | -0.744129 | 0.6615 | 0.6642 | 0.2879 | nan | nan |
| 2459981 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.513717 | 2.720584 | -0.210004 | -1.397613 | 1.455576 | -0.368633 | 0.318274 | -0.022344 | 0.5856 | 0.5844 | 0.3682 | nan | nan |
| 2459980 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.642895 | 2.391240 | -0.364168 | -1.453612 | -0.670854 | -0.934080 | -1.233244 | -1.444856 | 0.6338 | 0.6332 | 0.3029 | nan | nan |
| 2459979 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.513202 | 2.793822 | -0.344473 | -1.431536 | 1.363825 | -1.202497 | -0.151974 | -0.132233 | 0.5815 | 0.5819 | 0.3644 | nan | nan |
| 2459978 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.525308 | 3.690452 | -0.280237 | -1.428919 | 0.122545 | -0.452305 | -0.134279 | 0.251005 | 0.5808 | 0.5739 | 0.3724 | nan | nan |
| 2459977 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.477304 | 2.533332 | -0.303310 | -1.409510 | 1.059843 | -0.600469 | -0.460112 | -0.026340 | 0.5475 | 0.5450 | 0.3339 | nan | nan |
| 2459976 | not_connected | 0.00% | 0.00% | 0.00% | 0.00% | - | - | -0.334813 | 2.726433 | -0.494993 | -1.521305 | 1.944730 | -0.667410 | 0.297666 | -0.352683 | 0.5889 | 0.5880 | 0.3646 | nan | nan |
auto_metrics notebooks.¶htmls_to_display = []
for am_html in auto_metric_htmls:
html_to_display = ''
# read html into a list of lines
with open(am_html) as f:
lines = f.readlines()
# find section with this antenna's metric plots and add to html_to_display
jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
try:
section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
except ValueError:
continue
html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
for line in lines[section_start_line + 1:]:
html_to_display += line
if '<hr' in line:
htmls_to_display.append(html_to_display)
break
These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.
for i, html_to_display in enumerate(htmls_to_display):
if i == 100:
break
display(HTML(html_to_display))
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | -0.021670 | -0.021670 | -1.217124 | -1.315919 | -0.536486 | -0.950438 | -0.378832 | -0.130622 | -0.066986 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Discontinuties | 0.671223 | 0.271858 | -1.197958 | -1.209921 | -0.473943 | -0.764425 | -0.287555 | -0.056586 | 0.671223 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Discontinuties | 2.578954 | -0.923065 | 0.655349 | -0.922511 | -1.159732 | 0.334038 | -0.733697 | 2.578954 | 0.333649 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 0.322798 | -1.407297 | -0.030984 | -0.615244 | -1.329978 | 0.322798 | -0.265497 | -0.851625 | -0.436433 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | -0.161551 | -1.301787 | -0.161551 | -0.486829 | -1.459222 | -0.754782 | -0.250714 | -0.745751 | -0.616751 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Shape | nan | nan | nan | inf | inf | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | nan | nan | nan | nan | nan | nan | nan | nan | nan |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Discontinuties | 0.346730 | -0.903739 | 0.235142 | -0.336024 | -1.165780 | -0.506575 | -0.789389 | 0.346730 | -0.168208 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 0.136086 | -0.724379 | 0.136086 | 0.050466 | -1.153448 | -1.024379 | -0.821948 | -0.360455 | -0.409545 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | -0.046172 | -1.048155 | -0.046172 | -0.491167 | -1.173534 | -0.351141 | -0.676836 | -0.293716 | -0.355275 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Power | inf | 251.368927 | 251.390312 | inf | inf | 3295.470758 | 3294.782826 | 7716.389743 | 7713.477310 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 0.310606 | -0.801687 | 0.310606 | -0.169004 | -1.208889 | -0.473073 | -0.665875 | -0.080085 | 0.163766 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 5.535953 | -0.715404 | 0.395920 | -0.150201 | -1.353123 | 5.535953 | -0.530371 | 0.385604 | -0.469203 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 1.272804 | -0.603261 | 0.685740 | -0.215517 | -1.337504 | 1.272804 | -0.938272 | 0.833594 | 0.205311 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 0.673899 | 0.673899 | -0.473901 | -1.331626 | -0.073268 | -0.984190 | -0.038642 | -0.146128 | 0.192113 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 1.463889 | 0.723688 | -0.669825 | -1.001843 | -0.006582 | -1.109001 | 1.463889 | -0.392708 | 0.538090 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 0.826369 | 0.826369 | -0.787664 | -1.430071 | -0.071043 | -0.831839 | 0.065768 | -0.214164 | -0.308809 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 0.228336 | -0.972076 | 0.228336 | -0.211240 | -1.310179 | -0.542778 | -0.652055 | -0.853090 | -0.013743 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 1.087773 | 0.597970 | -0.976993 | -1.486124 | -0.226936 | -0.727994 | 1.087773 | -1.547479 | -0.576139 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 0.559127 | 0.312475 | -0.816103 | -1.358213 | -0.528669 | -1.162484 | 0.559127 | -0.430300 | 0.006813 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | ee Temporal Variability | 0.418826 | -0.631730 | 0.031208 | -0.866793 | -1.378836 | 0.418826 | -0.962083 | -1.272424 | -0.984932 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.229185 | -0.858002 | 2.229185 | -0.235428 | -1.329347 | 0.434885 | -0.640816 | 0.012368 | -1.109357 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 1.789049 | 0.480627 | 1.789049 | -1.145706 | -0.911906 | 0.787062 | -1.012047 | -0.671433 | -0.744129 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.720584 | 2.720584 | -0.513717 | -1.397613 | -0.210004 | -0.368633 | 1.455576 | -0.022344 | 0.318274 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.391240 | 2.391240 | -0.642895 | -1.453612 | -0.364168 | -0.934080 | -0.670854 | -1.444856 | -1.233244 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.793822 | -0.513202 | 2.793822 | -0.344473 | -1.431536 | 1.363825 | -1.202497 | -0.151974 | -0.132233 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 3.690452 | 3.690452 | -0.525308 | -1.428919 | -0.280237 | -0.452305 | 0.122545 | 0.251005 | -0.134279 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | ee Shape Modified Z-Score | nn Shape Modified Z-Score | ee Power Modified Z-Score | nn Power Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Discontinuties Modified Z-Score | nn Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.533332 | -0.477304 | 2.533332 | -0.303310 | -1.409510 | 1.059843 | -0.600469 | -0.460112 | -0.026340 |
| Ant | Node | A Priori Status | Worst Metric | Worst Modified Z-Score | nn Shape Modified Z-Score | ee Shape Modified Z-Score | nn Power Modified Z-Score | ee Power Modified Z-Score | nn Temporal Variability Modified Z-Score | ee Temporal Variability Modified Z-Score | nn Temporal Discontinuties Modified Z-Score | ee Temporal Discontinuties Modified Z-Score |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 132 | N11 | not_connected | nn Shape | 2.726433 | 2.726433 | -0.334813 | -1.521305 | -0.494993 | -0.667410 | 1.944730 | -0.352683 | 0.297666 |